Community for Data Integration (CDI)

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The Community for Data Integration (CDI) is a dynamic community of practice working together to grow USGS knowledge and capacity in scientific data and information management and integration.

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Join a group of peers to explore common interests and solve shared challenges.

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Projects and Products

The CDI supports innovative ideas across the community with seed funding for projects.

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Participate in monthly forums, topical discussions, trainings, or the annual proposals process.

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News

Date published: March 30, 2019

From Big Data to Smart Data: 2019 CDI Workshop Registration is Open

Registration is open for our 2019 Community for Data Integration Workshop, "From Big Data to Smart Data."

Date published: February 21, 2019

Twenty Community for Data Integration Proposals Advance to Phase 2

Thank you to all community members who submitted, commented on, or voted for the Statements of Interest! 

Date published: September 26, 2018

FY19 CDI Request for Proposals

Join us this fall for a unique community-driven process for building USGS capabilities in data integration and management.

Publications

Year Published: 2018

Community for Data Integration fiscal year 2017 funded project report

The U.S. Geological Survey Community for Data Integration annually funds small projects focusing on data integration for interdisciplinary research, innovative data management, and demonstration of new technologies. This report provides a summary of the 11 projects funded in fiscal year 2017, outlining their goals, activities, and outputs.

Hsu, Leslie; Allstadt, Kate E.; Bell, Tara M.; Boydston, Erin E.; Erickson, Richard A.; Everette, A. Lance; Lentz, Erika E.; Peters, Jeff; Reichert, Brian E.; Nagorsen, Sarah; Sherba, Jason T.; Signell, Richard P.; Wiltermuth, Mark T.; Young, John A.
Hsu, L., Allstadt, K.E., Bell, T.M., Boydston, E.E., Erickson, R.A., Everette, A.L., Lentz, E., Peters, J., Reichert, B.E., Nagorsen, S., Sherba, J.T., Signell, R.P., Wiltermuth, M.T., and Young, J.A., 2018, Community for Data Integration fiscal year 2017 funded project report: U.S. Geological Survey Open-File Report 2018–1154, 15 p., https://doi.org/10.3133/ofr20181154.

Year Published: 2018

Wrangling distributed computing for high-throughput environmental science: An introduction to HTCondor

Biologists and environmental scientists now routinely solve computational problems that were unimaginable a generation ago. Examples include processing geospatial data, analyzing -omics data, and running large-scale simulations. Conventional desktop computing cannot handle these tasks when they are large, and high-performance computing is not...

Erickson, Richard A.; Fienen, Michael N.; McCalla, S. Grace; Weiser, Emily L.; Bower, Melvin L.; Knudson, Jonathan M.; Thain, Greg
Erickson, R.A., Fienen, M.N., McCalla, S.G., Weiser, E.L., Bower, M.L., Knudson, J.M., Thain, G. 2018. Wrangling distributed computing for high-throughput environmental science: An introduction to HTCondor. PLoS Computational Biology. 14(10):e1006468. DOI: 10.1371/journal.pcbi.1006468.

Year Published: 2018

Community for Data Integration 2017 annual report

The Community for Data Integration (CDI) is a group that helps members grow their expertise on all aspects of working with scientific data. The CDI’s activities advance data and information integration capabilities in the U.S. Geological Survey and in the wider Earth and biological sciences. This annual report describes the presentations,...

Hsu, Leslie; Langseth, Madison L.
Hsu, L., and Langseth, M.L., 2018, Community for Data Integration 2017 annual report: U.S. Geological Survey Open-File Report 2018–1110, 19 p., https://doi.org/10.3133/ofr20181110.